| Feature detection |
|---|
| Edge detection |
| Corner detection |
| Blob detection |
| Ridge detection |
| Hough transform |
| Structure tensor |
| Affine invariant feature detection |
| Feature description |
| Scale space |
Affine shape adaptation is a methodology for iteratively adapting the shape of the smoothing kernels in an affine group of smoothing kernels to the local image structure in neighbourhood region of a specific image point. Equivalently, affine shape adaptation can be accomplished by iteratively warping a local image patch with affine transformations while applying a rotationally symmetric filter to the warped image patches. Provided that this iterative process converges, the resulting fixed point will be affine invariant. In the area of computer vision, this idea has been used for defining affine invariant interest point operators as well as affine invariant texture analysis methods.